The statements in this section merely provide background information related to the disclosure and may not constitute prior art.
Healthcare environments, such as hospitals or clinics, include information systems, such as hospital information systems (HIS), radiology information systems (RIS), clinical information systems (CIS), and cardiovascular information systems (CVIS), and storage systems, such as picture archiving and communication systems (PACS), library information systems (LIS), and electronic medical records (EMR). Information stored may include, for example, patient medication orders, medical histories, imaging data, test results, diagnosis information, management information, and/or scheduling information, for example.
Protocol-centric environments are institutions such as hospitals, step down facilities, nursing and private homes, and the like. A hospital is used herein as an example of a protocol-centric environment. Adverse events that occur in hospitals, such as, for example, hospital-acquired pneumonia, result in patient harm, increased recovery time, unreimbursed healthcare costs, and loss of a hospital's and its staff's capacity to serve. One of the main causes of these events is non-adherence to protocols. As used herein, protocols refer to a series of preferred or prescribed tasks that (1) have been proven to reduce adverse events and (2) effect a desired elimination of activities, practices, or patterns that create harm or inefficiency. Example uses of such protocols are for hand washing, tube management (ventilator, urinary tract, and central line being examples), spirometry, and physical therapy. Protocols may be dually managed with a shared sensing and control system. For example, lung function protocols, having a shared attribute of being focused on breathing with aid of an apparatus interacting with the patient's nose, mouth, lungs and pulmonary biological/physical systems, can be managed together via a shared sensing and control system.
As an illustrative example, despite widespread knowledge that proper care plans, such as those for ventilators have associated protocols, which if followed, also reduce adverse events. Mortality rates for ventilator associated or acquired pneumonia that can be attributed to breaches in patient position and ventilator tube changing protocols range from approximately 25%-50% and can reach up to 76% in specific settings in the institutional care setting today, such as in hospitals. Estimates of the costs for one case of ventilator-associated pneumonia (VAP) have been reported to be $10,000-$16,000 adding an estimated 4-32 additional ventilator days. Harm is therefore inflicted on the patient and a healthcare institution's ability to serve is diminished.
While there are many reasons for non-compliance (including a perceived lack of risk, time to wash, missing knowledge of protocol, or associated discomfort from complying with protocol and general inconvenience) improvement in protocols for hand sanitization before coming in contact with patients, mouth and skin care, tube exchange and lung exercise will reduce the spread of bacteria and thus lower the incidence of adverse events, thereby improving the standard of care. It is therefore advantageous to help the providers of healthcare and other persons involved in a patient's care or visitation to comply with protocols, including the patient themselves.
Many procedures benefit from a higher frequency of protocol compliance. Even relatively low level and treatable infections, such as a urinary tract infection, can escalate to life-threatening conditions including sepsis. Protocols to change tubes, if followed, will reduce the incidence of opportunities leading to infection onset. Protocols to ensure lung exercise will maximize the likelihood that air exchange capability is created.
Systems that have been developed to track and analyze activities in a clinical setting have focused primarily on single modality sensing, for example, Radio Frequency Identification (RFID) or infrared (IR) or manual key input or written bed board updates or human observatory monitoring schemas. As an example, one known RFID-based system focuses on identifying human activities in a hospital environment using Hidden Markov Models (HMMs) for supporting context-aware applications. While some manufacturing systems may incorporate a combination of RFID and computer vision, the multiple sensors are used to produce a discrete snapshot in time and do not provide contextual information over a period of time.
Typically, RFID and other protocol sensor systems take the form of location and contact make/break or pressure sensing for certain protocol adherence assuming that location association equates to protocol delivery or proper use of biomedical equipment by patients and care providers. This is a considerable failure point. As one example, an institution may specify that staff shall sanitize their hands upon entrance into the patient's room. Since there is little or no mechanism to reason what the staff is doing in the room or context, simple non-nuanced standing procedures are enforced. Sensor systems such as those that are IR or RFID-based determine if staff was in the presence of a hand sanitization station, or if cleansing agents are dispensed. A process defect is alarmed or recorded when staff enter a room and do not sanitize. In other systems, the provider of care wears a device to display they have hand sanitized but partially leave the protocol adherence determination to the patient for warning the care provider.
In non-healthcare domains, such as commercial shopping monitoring, humans in effect become the sensors with such programs as ‘secret shoppers’ and behavioral studies that use shopping patterns to infer consumer propensities to select product preferentially.
However, in such single modality systems a sensor must be associated with the patient, care provider, or apparatus being monitored, and infer that the proper contact has been made for a requisite time and orientation and clinical result. Further, such systems do not provide specific corrective control regarding specific behaviors, actions, and in-situ feedback. RFID systems are further limited by their range; typically RFID systems have a certain range of tolerance with respect to a tag (not hands or apparatus or contact) location.
In systems that employ optical sensing, optical tags may be used to identify objects such as specific equipment, patients, care providers, and sundry apparatus. Such systems typically provide optical or other tag information to a sensor and/or video record, may superimpose such information on a display, or may identify the orientation of a plurality of reference points for optical positioning for the purposes of diagnostic imaging or placement of apparatus such as biopsy needles but do not provide contextual guidance and incentives.
Therefore, it would be desirable to design a system and method for protocol adherence which precisely tracks, over time, hand surface, apparatus position, and dynamical action context with respect to tasks prescribed in the protocol, so that care protocols may be intervened into in real time and may be used for engaging the patient and be used for staff skill building—ultimately enabling superior medical outcomes in delivery of care by personnel who are tasked with ever more acute cases and census. Further that the control system would provide incentives for patients through time to stay on protocol for those who can self administer while for those patients who are impaired, the system would tightly control the delivery of care by other persons or mechanical systems. Such tracking, engagement, control, intervention, and improvement cannot be found in the prior art.